Getting linear time in graphs of bounded neighborhood diversity
Parameterized complexity, introduced to efficiently solve NP‐hard problems for small values of a fixed parameter, has been recently used as a tool to speed up algorithms for tractable problems. Following this line of research, we design algorithms parameterized by neighborhood diversity (nd$$ \maths...
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Published in | Networks Vol. 84; no. 3; pp. 255 - 277 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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Hoboken, USA
John Wiley & Sons, Inc
01.10.2024
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Abstract | Parameterized complexity, introduced to efficiently solve NP‐hard problems for small values of a fixed parameter, has been recently used as a tool to speed up algorithms for tractable problems. Following this line of research, we design algorithms parameterized by neighborhood diversity (nd$$ \mathsf{nd} $$) for several graph theoretic problems in P$$ P $$: Maximum b$$ b $$‐Matching, Triangle Counting and Listing, Girth, Global Minimum Vertex Cut, and Perfect Graphs Recognition. Such problems are known to admit algorithms parameterized by modular‐width (mw$$ \mathsf{mw} $$) and consequently—as nd$$ \mathsf{nd} $$ is a special case of mw$$ \mathsf{mw} $$—by nd$$ \mathsf{nd} $$. However, the proposed novel algorithms allow for improving the computational complexity from time O(f(mw)·n+m)$$ O\left(f\left(\mathsf{mw}\right)\cdotp n+m\right) $$—where n$$ n $$ and m$$ m $$ denote, respectively, the number of vertices and edges in the input graph—to time O(g(nd)+n+m)$$ O\left(g\left(\mathsf{nd}\right)+n+m\right) $$ which is only additive in the size of the input. Then we consider some classical NP‐hard problems (Maximum independent set, Maximum clique, and Minimum dominating set) and show that for several classes of hereditary graphs, they admit linear time algorithms for sufficiently small—nonnecessarily constant—values of the neighborhood diversity parameter. |
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AbstractList | Parameterized complexity, introduced to efficiently solve NP‐hard problems for small values of a fixed parameter, has been recently used as a tool to speed up algorithms for tractable problems. Following this line of research, we design algorithms parameterized by neighborhood diversity (nd$$ \mathsf{nd} $$) for several graph theoretic problems in P$$ P $$: Maximum b$$ b $$‐Matching, Triangle Counting and Listing, Girth, Global Minimum Vertex Cut, and Perfect Graphs Recognition. Such problems are known to admit algorithms parameterized by modular‐width (mw$$ \mathsf{mw} $$) and consequently—as nd$$ \mathsf{nd} $$ is a special case of mw$$ \mathsf{mw} $$—by nd$$ \mathsf{nd} $$. However, the proposed novel algorithms allow for improving the computational complexity from time O(f(mw)·n+m)$$ O\left(f\left(\mathsf{mw}\right)\cdotp n+m\right) $$—where n$$ n $$ and m$$ m $$ denote, respectively, the number of vertices and edges in the input graph—to time O(g(nd)+n+m)$$ O\left(g\left(\mathsf{nd}\right)+n+m\right) $$ which is only additive in the size of the input. Then we consider some classical NP‐hard problems (Maximum independent set, Maximum clique, and Minimum dominating set) and show that for several classes of hereditary graphs, they admit linear time algorithms for sufficiently small—nonnecessarily constant—values of the neighborhood diversity parameter. Abstract Parameterized complexity, introduced to efficiently solve NP‐hard problems for small values of a fixed parameter, has been recently used as a tool to speed up algorithms for tractable problems. Following this line of research, we design algorithms parameterized by neighborhood diversity () for several graph theoretic problems in : Maximum ‐ Matching , Triangle Counting and Listing , Girth , Global Minimum Vertex Cut , and Perfect Graphs Recognition . Such problems are known to admit algorithms parameterized by modular‐width () and consequently—as is a special case of —by . However, the proposed novel algorithms allow for improving the computational complexity from time —where and denote, respectively, the number of vertices and edges in the input graph—to time which is only additive in the size of the input. Then we consider some classical NP‐hard problems ( Maximum independent set , Maximum clique , and Minimum dominating set ) and show that for several classes of hereditary graphs, they admit linear time algorithms for sufficiently small—nonnecessarily constant—values of the neighborhood diversity parameter. |
Author | Rescigno, Adele A. Cordasco, Gennaro Gargano, Luisa |
Author_xml | – sequence: 1 givenname: Gennaro orcidid: 0000-0001-9148-9769 surname: Cordasco fullname: Cordasco, Gennaro email: gennaro.cordasco@unicampania.it organization: Università della Campania “L. Vanvitelli” – sequence: 2 givenname: Luisa orcidid: 0000-0003-3459-1075 surname: Gargano fullname: Gargano, Luisa organization: Università di Salerno – sequence: 3 givenname: Adele A. orcidid: 0000-0001-9124-610X surname: Rescigno fullname: Rescigno, Adele A. organization: Università di Salerno |
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Snippet | Parameterized complexity, introduced to efficiently solve NP‐hard problems for small values of a fixed parameter, has been recently used as a tool to speed up... Abstract Parameterized complexity, introduced to efficiently solve NP‐hard problems for small values of a fixed parameter, has been recently used as a tool to... |
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SubjectTerms | Algorithms Apexes Complexity Graph theory Graphs hereditary graph classes neighborhood diversity Neighborhoods Parameterization parameterized complexity Parameters |
Title | Getting linear time in graphs of bounded neighborhood diversity |
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